CAREER: Design of Two-sided Markets In Dynamic and Uncertain Environments: Theoretical and Operational Issues

职业：动态和不确定环境中双边市场的设计：理论和操作问题

• 批准号: 1351821
• 负责人: Mustafa Akan
• 金额: $ 40.06万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1351821&HistoricalAwards=false
• 关键词: CAREER; Design; Two; sided; Markets

The research objective of this Faculty Early Career Development (CAREER) Program award is to study the design of two-sided markets in dynamic and uncertain settings. The population of agents in the system evolves over time due to stochastic arrivals to both sides of the market. Agents report their preferences upon entering the system, and either accept or reject match offers based on the compatibility of preferences as well as value of future options. The primary goal of this award is to design such marketplaces in an efficient way by taking into account dynamic interaction, uncertainty and forward looking behavior of agents. The research approach is to compute each agent's expected benefit from remaining unmatched as a utility promise from the market designer under a given policy, which will enable an algorithm for (dynamically) individually-rational match offers. The algorithm will be generalized to the environment where agents may not know their true preferences over matches before the match and there are multiple matches generated on both sides. Further analysis will endow agents with straightforward incentives for truthful behavior and consider the possibility that a market designer learns about agent preferences by observing their responses to match offers while the agents learn about the distribution of available partners by observing the offers they get.If successful, the results of this research will lead to improvements in the layout of markets where there is a need to match two-sided populations of agents such as labor markets, organ transplant, child adoption, and foster care. The award can provide modeling and analysis tools to maximize the efficiency of the matching system and the welfare of its participants. The research is made possible by combining tools developed both in matching/market design in economics and those commonly used in operations. The mathematics developed will also help train graduate and undergraduate students as well as contribute to an ongoing private public partnership between Carnegie Mellon and Pennsylvania Adoption Exchange (PAE).

该学院早期职业发展（CAREER）计划奖项的研究目标是研究动态和不确定环境中双边市场的设计。由于随机到达市场双方，系统中的代理数量会随着时间的推移而变化。代理在进入系统时报告他们的偏好，并根据偏好的兼容性以及未来选项的价值接受或拒绝匹配报价。该奖项的主要目标是通过考虑代理商的动态交互、不确定性和前瞻性行为，以有效的方式设计此类市场。研究方法是计算每个代理在给定政策下保持不匹配的预期收益，作为市场设计者的效用承诺，这将为（动态）个人理性匹配报价提供算法。该算法将推广到这样的环境：智能体在比赛前可能不知道自己对比赛的真实偏好，并且双方都会生成多个比赛。进一步的分析将为代理商提供诚实行为的直接激励，并考虑市场设计者通过观察代理商对匹配报价的反应来了解代理商偏好的可能性，而代理商则通过观察他们获得的报价来了解可用合作伙伴的分布。如果成功，这项研究的结果将导致市场布局的改善，这些市场需要匹配劳动力市场、器官移植、儿童收养和寄养等两侧群体的代理人。该奖项可以提供建模和分析工具，以最大限度地提高匹配系统的效率及其参与者的福利。通过结合经济学匹配/市场设计中开发的工具和运营中常用的工具，使这项研究成为可能。所开发的数学还将帮助培训研究生和本科生，并为卡内基梅隆大学和宾夕法尼亚收养交易所（PAE）之间持续的私人公共合作伙伴关系做出贡献。

项目成果

Revenue management by sequential screening

• DOI: 10.1016/j.jet.2015.07.016
• 发表时间: 2015-09
• 期刊: J. Econ. Theory
• 作者: Mustafa Akan;B. Ata;James D Dana